Waste Detection 2.0 Computer Vision Project

Here's a description for your "Waste Detection 2.0" computer vision project and dataset:

Dataset Name: Waste Detection 2.0

Data Source: This dataset is designed for waste detection in various settings, with a focus on identifying different types of waste materials.

Last Updated: An hour ago (as of the most recent update).

Project Type: Object Detection

Subject: The dataset focuses on the detection and classification of waste materials, specifically including the following classes:

1. Bottle
2. Can
3. Carton
4. E-Waste
5. Electric Cable
6. Glass
7. Glass Bottle
8. Metal
9. Organic Waste
10. Phone Case
11. Plastic Bag
12. Plastics
13. Spoon
14. Styrofoam
15. Trash
16. Trash-Brush
17. Wooden Waste
18. Yoga Mat
19. Paper

Content: The dataset contains a diverse range of waste materials, encompassing items such as bottles, cans, cartons, electronic waste, cables, glass, metal, organic waste, phone cases, plastic bags, various plastic items, spoons, styrofoam, trash items, wooden waste, yoga mats, and paper.

Size: The size of the dataset in terms of the number of images or data points is not specified.

Annotations: It is implied that the dataset includes annotations for object detection, which would likely involve bounding boxes or object masks for the waste materials.

Purpose: The purpose of this dataset is to facilitate object detection tasks, particularly focused on waste material classification. This can have applications in environmental monitoring, waste sorting, and related computer vision projects.

License:

*The "Waste Detection 2.0" dataset is made available under the following license terms: *

1. License Holder: Sakib Hossain
2. Contact Email: sakib.cse.aiub@gmail.com

Terms and Conditions:

By accessing or using the "Waste Detection 2.0" dataset, you agree to the following terms and conditions:

1. Usage Rights: You are granted the right to use, modify, and distribute the dataset for research, educational, and non-commercial purposes only.

2. Attribution: When using or sharing the dataset or any derived work, you must provide proper attribution to Sakib Hossain as the dataset holder. Please include the dataset name and a reference to the source.

3. Non-Commercial Use: The dataset may not be used for commercial purposes without prior written consent from Sakib Hossain.

4. Distribution: If you distribute the dataset or any modified version of it, you must ensure that these terms and conditions are included with the dataset.

5. No Warranty: The dataset is provided "as is," without any warranty or guarantee of accuracy or completeness. Sakib Hossain is not liable for any damages or losses resulting from the use of the dataset.

6. Usage of Personal Information: By using this dataset, you acknowledge and agree that your contact email (sakib.cse.aiub@gmail.com) may be used by Sakib Hossain for communication related to the dataset, updates, or other relevant information.

These terms and conditions are subject to change. It is your responsibility to check for updates to the terms and conditions periodically.

For any inquiries or requests regarding commercial use, licensing, or further information about the dataset, please contact Sakib Hossain at sakib.cse.aiub@gmail.com.

This dataset appears to be a valuable resource for training and evaluating computer vision models designed to recognize and classify various types of waste materials, which can contribute to waste management and environmental sustainability efforts.

                        @misc{
                            waste-detection-2.0-hwohv_dataset,
                            title = { Waste Detection 2.0 Dataset },
                            type = { Open Source Dataset },
                            author = { Sakib },
                            howpublished = { \url{ https://universe.roboflow.com/sakib-9bfzb/waste-detection-2.0-hwohv } },
                            url = { https://universe.roboflow.com/sakib-9bfzb/waste-detection-2.0-hwohv },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-11-21 },
                            }